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Everything posted by hnn12

I am in the same situation without Rutgers. As to the placements of PhD graduates at UC Davis, I asked the program coordinator and she gave me a list of placements last year. It seems like most people (80-90%) go into industry. I prefer to work in industry after graduation, so the placements at UC Davis is very appropriate for me, but Rice seem to do equally well with regards to this aspect. UC Davis is close to Sacramento, which is a much smaller city, but it only takes less than 2 hours of drive to get to San Francisco and the tech hub in Palo Alto. However, Rice has the edge for me with regards to location because I am kinda a big-city boy and Houston is nice yet low-cost city. There are many outstanding professors that I want to work with at UC Davis (Thomas Lee for one), but Rice has Genevera Allen, who is a rising star in the field (and her advisor is Robert Tibshirani from Stanford). The thing I like most about Rice is that the department allows well-prepared PhD students to take the qualifying exam right at the beginning of the first year. The exam is based on Casella & Berger, and there is a high chance that you can finish your PhD within 4 years if you pass it. Overall, I am leaning towards Rice slightly, but UC Davis gave me a really good financial package. And I have other universities in the equation, too.

In addition to what @Geococcyx said, you can try some Bioinformatics programs, which emphasize the computational aspect more. I have a friend who got into a reasonable PhD Bioinformatics program without any research experience and knowledge in biology. She has a light Maths background and come from an institution that is not known outside my country. That said, she got a higher GPA than you, so I am not sure how your chances are at PhD Bioinformatics, but you can give it a shot if you want. Perhaps more experienced members of the forum can give you more insights.

I think it will be very, very tough for you to get into a reasonably good PhD program in Statistics. Your Master GPA is good, but it cannot make up for your Undergrad GPA. This is more so because your Undergrad was done in the US whereas your Master is in another country. I am an applicant this year, and I also got my education in the UK. My impression is that the admission committees are usually not familiar with our grading system. I know that Warwick has a fantastic Maths department and it is a great achievement to get 4.0 from them, but the adcoms may not have that knowledge. Furthermore, advanced Maths courses, especially Real Analysis and Linear Algebra, are much more important than Applied Statistics courses. You are an international student, so it is even tougher for you, given that you have no research experience.
My suggestion is that you can try some PhD programs in Biostatistics. The required Maths background for PhD Biostatistics is much lighter than PhD Statistics. You can consider taking the GRE Maths Subject Test and try to absolutely ace it. To some extent, it can help alleviate the adcoms' concern about your Maths background. Another option for you is to do another Master degree in the US and try to get the most out of it (advanced coursework, research experience and connection with profs).

I think that you are aiming at reasonable schools. I suggest adding schools like UC Davis, Rice and UC Riverside to your list. I cannot recommend more without additional information like your research interests. With regards to your application, I think your Master GPA will be a negative point to the admission committee because it shows a downward trend from your undergrad and the average GPA for Master is around 3.8 if I remember correctly. This is more so for you because you are an international students, and the competition among us is real. IMO, I think top-30 schools in the US News ranking are reaches for you, but you can try a few schools in the top 40. Schools at the level of Florida State and UFL are reasonable, but you may want to add some lower-ranked schools like UC Riverside as safety choices. You have a good undergrad GPA, so I am pretty sure you will get in somewhere if you spread your applications widely.

Both are amazing schools and you can't go wrong with either. IMO, it depends on what area of Statistics you want to pursue. Chicago is very, very theoretical and their curriculum contains a heavy amount of maths, so it is great if you want to focus on statistical theory. You can double-check what I have said by looking at the list of faculty members at Chicago. Stanford, on the other hand, is very strong in Machine Learning and you can find great opportunities to have hand-on experience in ML at one of the companies / startups in the Bay area. Overall, I think that Stanford is more balanced between theory and application, and it is a better choice if you are not yet sure about the kind of research you want to do in the future. I have a friend, who did his MS in Statistics at Stanford. He got a summer internship in data science at Adobe. Now, he is doing his PhD in Statistics at Chicago. You can be assured that Stanford has an excellent record in sending their students to top PhD programs.

Yes, your chance is significantly better with Linear Algebra on your transcript.
The adcoms at top schools will much prefer proof-based courses in Linear Algebra. Some schools like Berkeley and Wisconsin explicitly ask you to submit a separate document that lists all the maths courses you have done, including the textbooks you use, so they can certainly check if your courses are proof-based or not. For most schools, they do not ask you to submit this document. Unfortunately, this is why the prestige of undergrad institution is so important for top schools. It is difficult to judge the quality of a course just from its title on the transcript. They also don't know about the grading scale at your university (is 90% high or not???). If you come from a prestigious school, the adcoms are familiar with the rigor of the maths courses at your school (as well as the grading system) and they are much more likely to admit you. In your case, if your school is not well-known in the US, you can mitigate this problem by making sure that your recommenders emphasize your maths skills in their letters and, if possible, state your position relative to other students in the cohort. That will help you a lot for top-20 schools like PSU and UMN. The lower you go down the US News ranking, the less important it is to have proof-based courses. You will be fine at schools like OSU and UF.
I am an applicant this year myself and I have been admitted to UC Davis, so I can give you some information on their programs. They have very strong programs in Agriculture / Environment / Ecology, so it is a good place if you want to study the application of Statistics to these areas. In fact, I think it is a top-3 school in Agriculture globally. I asked the program coordinator about the placements of PhD graduates from UC Davis. 80-90% of the PhDs go into industry, just like what the professor told me in the interview. I recognize that many of them become data scientists for tech companies / startups, probably due to the university's proximity to tech hubs in California. If you want to work with Ethan Anderes, you should make sure that he actually takes part in supervising PhD students. Keep in mind that PhD Statistics is very different from some other disciplines (e.g. PhD Comp Sci) in that you are admitted to the department, not the professor's lab. So, there is no guarantee that you can work with a particular professor once you get there.
Unfortunately, I am not familiar with Canadian programs, so I can't help you with that.

IMO, your list of schools matches really well with your research interests. I would highly recommend you to apply to UConn and Purdue, too. They have some good faculty members in your chosen areas. For example, Purdue has Bruce Craig and Tonglin Zhang.
I think that your GPA is great, and the fact that your undergrad institution is in Canada will probably help, as most US professors are familiar with the Canadian grading system. The weakest point in your application is probably your lack of advanced maths courses. I see that you have done Real Analysis, but you need to have Linear / Abstract Algebra on your transcript too, as most applicants in top schools do. Your GRE score is on the lower side, so you can try to improve it if you have time. As an international student myself, I can feel that the competition among us is very, very fierce. For these reasons, I think that schools at the caliber of PSU, UMN and Purdue are reaches for you, but you can certainly try a few of those. Schools like OSU, UConn and UF are realistic.

No consultant in this world can fix your transcript and LoR, which are the most important components in your applications. Competition among international students has got to a point where top GPA, prestigious undergrad institution and good LoR can only get you into consideration at top schools. They have many people with perfect GPA, so you need extra things to stand out. To be accepted at those schools, you need strong research experience, excellent LoR from well-known professors, and a bit of luck too. I don't see how a consultant can help you with those. If the OP has $3,000 to spend, I would advice him to use that money and apply to 30 schools across the US News ranking. I am sure that he will get into a few places with that GPA, publication and a prestigious MS. He is certainly competitive for top-40 schools.

I will echo the advice that has been given to you. I am an applicant this year and the competition among international students has really struck me very hard. I know people with stellar profiles, who got rejected by top-10 schools. You can increase your chance (significantly) by applying to larger PhD Statistics programs such as OSU, UConn, UF and Florida State. They have good faculty members in missing data and causal inference. Keep in mind that most students actually change their research directions after a few years into their PhDs. Don't bother applying to small programs like Yale, Northwestern and NYU. They have relatively low ranking in US News, but are very difficult to get in due to small admission quota. Apart from NCSU, you can try a few other reach schools like Penn State and TAMU.
With regards to your standardized tests, I would rather try to get a good score in the Maths Subject Test than retaking the general GRE. Most adcoms know that performance in the quant section of the GRE is a bad indicator of success at graduate schools and the 165 will not jeoparize your application. I got 970 in the Maths Subject Test and the adcom at Rice explicitly said that they were very impressed by my performance. I am also pretty sure that the score has helped me to secure several offers at some top-20 schools. The Subject Test is especially useful if your maths background is light and your undergrad institution is not well known in the US. After all, a single PhD student takes a lot of funding, and the adcoms don't want to bet on someone whose records they do not understand. IMO, you should only send your score if you get above 80th percentile.

I think contacting professor in advance matters much more in disciplines such as Computer Science, where students are admitted to professors' lab (and thus funded by professors). In such cases, you are likely to get in if the professors really want to have you in their labs. In Statistics, it is the departments that make admission decisions. That said, I still dropped professors' names in my SOP and so far, they have always appeared in my interviews (if there was one).

I think they mean only PhD applications. Given that Penn State is a popular school, I am not surprised that they receive that many applications.
I am not sure if Harvard even does waitlisting. Not seemed to happen in the past few years.

You are the one who really needs to revise your logical reasoning. People are saying that a good score in the GRE subject test MAY OR MAY NOT help you, depending on the admission process behind the scene, which we don't know. Some schools don't put a lot of emphasis in it and the score, therefore, doesn't help even if it's amazing. But others may need it. That's why Stanford explicitly requests it for the PhD program in Statistics. But you are making the bold claim that submitting it WILL NOT help and CAN ONLY hurt the applicant. A good score may not help, but it doesn't mean the adcom will punish you for having it.
OK, if I understand you correctly, you are saying that the GRE is a discrimination against certain races and gender, and one should not take part in it because it's morally wrong. Then you can just voice your opinion frankly. Trust me, everyone is aware that it's a bad test and nowhere near an indicator of success. Don't support your own cause by making misleading statements.

I'm an international student who graduated from the UK in 2016. I'm applying for PhD programs in Biostatistics/Statistics, starting Fall 2019. Please leave some comments on my profile, especially the range of schools to which I'm applying. BSc Degrees: Mathematics with specialization in Statistics from a top-10 university worldwide GPA: Top 10/~250
Master Degree: Finance from a top-10 university worldwide GPA: Top 10/~40
Type of student: Asian male
Program desired: PhD in Statistics/Biostatistics
Research Experience: coauthor of one published paper on an international journal in econometrics. I have also done 2 research projects (~ 3 months each) that were outsourced by private companies. Both were related to Statistics/Data Analysis. During undergraduate studies, I had 1 individual poster project, in which I made a poster on statistical classification using LaTeX and presented to faculty members, 1 group project on Support Vector Machine and Kernel Smoothing, which also involved writing a report and presented our work to professors, and 1 individual project on Pattern Recognition, which heavily involved R programming.
Teaching: 2 semesters of TA in Probability & Statistics and Time Series. I will TA another 2 semesters this year
LOR: 1 from my professor in the UK, who was my personal tutor. 1 from a professor, who is currently the director of the research institution I'm working at. Both should be strong. I can get the last letter from another professor, but whether it's strong or not is a question mark.
Programming: Proficient in R, MATLAB. Competent in C++, Visual Basic. Proficient in LaTeX
GRE: Verbal 162, Quantitative 170, Writing 5.0 GRE Subject Math: 820. Not sure if I should retake
Coursework: most were A+, some were A and 1 B in Computational Maths. My first 2 years focused on developing a rigorous mathematical background while my final year consisted of graduate level courses, mainly in advanced Statistics.
First year: Foundation of Analysis, Mathematical Methods I, Mathematical Methods II, Computational Maths, Mechanics, Probability and Statistics I, Geometry and Linear Algebra, Algebra I, Real Analysis
Second year: Probability and Statistics II, Algebra II, Introduction to Numerical Analysis, Analysis I, Complex Analysis, Statistical Modelling, Differential Equations, Multivariate Calculus
Third year: Statistical Pattern Recognition, Applied Statistics, Stochastic Simulation, Credit Scoring I, Scientific Computing in C++, Quantitative Finance, Survival Analysis, Games Risk & Decisions
Research Interests: I'm interested in high-dimensional statistics and machine learning, with applications to chronic diseases and cancer research in particular Applying to:
Biostatistics:
Harvard
UNC
Wisconsin-Madison (biostatistics track)
Minnesota - Twin Cities
Rochester Statistics:
CMU (joint statistics and machine learning)
Yale
Cornell
North Carolina State
Michigan - Ann Abor
Ohio State
Penn State Note: I'm currently working for a research institution, which is part of the national university in my country. I expect some more projects in this academic year, though I'm not sure if these result in publications. It's unlikely that these will come before the application deadlines anyways.
The things that concern me most is the questionable 3rd LOR and the lack of published papers (only 1 for me). I've also heard that chances are much slimmer for international students.

Thanks for your replies. Many people have warned me about the more limited chance at Biostats programs, so I have been revising my list of schools. All programs are PhD Statistics. I intend to apply to
Harvard, Chicago, Cornell, CMU, Upenn, Michigan, UNC, NCSU, Penn State, Iowa State, Purdue, Wisconsin-Madison, UCLA, Ohio State, UConn
Please share your thought on my list. Are there any particular programs that I should apply to, given my background above

I would like to ask for your opinion regarding my application for PhD programs in Biostatistics 2019. All programs seem to require strong background in mathematics, demonstrated by several semesters in Linear Algebra, Advanced Calculus, ideally Real Analysis and Numerical Analysis as well. Some top programs seem to favor students with previous experience in programming languages such as Python, R or MATLAB.
However, I am not sure if PhD programs in Biostatistics also require previous exposure to Biology and/or Genetics of any sorts. I graduated with a bachelor and a master degree with heavy mathematical/statistical components from a top UK institution (my bachelor degree was in fact mathematics with specialization in statistics). But I am not sure if the lack of formal training in biology will be a big disadvantage to me when applying for top Biostatistics programs.
Apart from PhD programs in Biostatistics, I am also applying to Statistics programs, where there are faculty members with interests in biomedical sciences.
Thanks very much for your opinions.